• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.1
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• pp.44-49
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• 2002

In recent years, diagnostic techniques have been investigated to detect a partial discharge(PD) in a high voltage electrical equipment. Because PD signal is very sensitive and difficult to suppress strong noises such as narrow-band radio frequency noise and random noise, the accuracy and credibility of PD measurement might be influenced by surrounding interference. Using the technique of PD detection by electromagnetic wave, we have studied the characteristics of both PD and substation-in interference signal. Also, we propose a wavelet packet transform based technique to perform a feature extraction from the interference and PD signal and a classification of the extracted features. The results show that time-frequency characteristics between PD and interference can be obviously distinguished. It is helpful for the development of the insulation diagnosis technique.

• Journal of the Korean Society of Safety
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• v.27 no.1
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• pp.7-13
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• 2012

This paper describes the diagnosis techniques using UV images taken in the field under energized condition of power equipments in order to figure out and analyze the abnormal states on the terminals of power equipments. To classify the features of the terminals, the counted No. of the corona generated at the terminals is defined. According to the result detected, the No. of corona detected on the power equipments installed inside a building is less than that installed outside a building, and it strongly depends on the environment and installed condition. Thus, the environmental condition needs enhanced, and stable operation by the periodic inspection under energized condition of the power equipments is required. Especially, the event counting technique using UV camera is useful for the power equipments apart more than 20 m to apply, and there can be an error due to the features of the sensing techniques when the distance between the user and the objects is close less than 15 m. Therefore, the experimental result shows that event counting technique is employed in the case of the distance more than 15 m. The electrical safety can be ensured by using the UV detection technique and the criteria.

• Smart Structures and Systems
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• v.3 no.2
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• pp.201-217
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• 2007

An active damage detection technique is introduced to locate damage in an isotropic plate using Lamb waves. This technique uses a time-domain energy model of Lamb waves in plates that the wave amplitude inversely decays with the propagation distance along a ray direction. Accordingly the damage localization is formulated as a least-squares problem to minimize an error function between the model and the measured data. An active sensing system with integrated actuators/sensors is controlled to excite/receive $A_0$ mode of Lamb waves in the plate. Scattered wave signals from the damage can be obtained by subtracting the baseline signal of the undamaged plate from the recorded signal of the damaged plate. In the experimental study, after collecting the scattered wave signals, a discrete wavelet transform (DWT) is employed to extract the first scattered wave pack from the damage, then an iterative method is derived to solve the least-squares problem for locating the damage. Since this method does not rely on time-of-flight but wave energy measurement, it is more robust, reliable, and noise-tolerant. Both numerical and experimental examples are performed to verify the efficiency and accuracy of the method, and the results demonstrate that the estimated damage position stably converges to the targeted damage.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2439-2450
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• 1997

As recording densities increase in digital magnetic recording channels, the performances of digital detection techniques such as PRML and DFE degrade significantly due to nonlinear distortion in recording channels. The primary impediments for hgih-density recording are generally classified as nonlinear transition shift, which can be reduced substantially by the precompensation technique, and partial erasure which usually requires sophisticated nonlinear equalization techniques. In order to acheieve the highest density recording, accurate estimation of the parameters associated with these two noninear distortions is crucial. In this paper, a new estimation technique to distinguish these two different nonlinear effect using a proposed adaptive algorithm in time domain is presented. The effectiveness of the proposed adaptive approach to identify uniquely the nonlinear parameter with bias is demonstrated by computer simulation.

• Proceedings of the KSRS Conference
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• v.2
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• pp.643-646
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• 2006

This paper addresses the approach to extract linear features from satellite imagery using an efficient segmentation method. The extraction of linear features from satellite images has been the main concern of many scientists. There is a need to develop a more capable and cost effective method for the Iranian map revision tasks. The conventional approaches for producing, maintaining, and updating GIS map are time consuming and costly process. Hence, this research is intended to investigate how to obtain linear features from SPOT satellite imagery. This was accomplished using a discontinuity-based segmentation technique that encompasses four stages: low level bottom-up, middle level bottom-up, edge thinning and accuracy assessment. The first step is geometric correction and noise removal using suitable operator. The second step includes choosing the appropriate edge detection method, finding its proper threshold and designing the built-up image. The next step is implementing edge thinning method using mathematical morphology technique. Lastly, the geometric accuracy assessment task for feature extraction as well as an assessment for the built-up result has been carried out. Overall, this approach has been applied successfully for linear feature extraction from SPOT image.

• Structural Monitoring and Maintenance
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• v.3 no.3
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• pp.297-314
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• 2016

As the study of internal corrosion of pipeline need a large number of experiments as well as long time, so there is a need for new computational technique to expand the spectrum of the results and to save time. The present work represents a new non-destructive evaluation (NDE) technique for detecting the internal corrosion inside pipeline by evaluating the dielectric properties of steel pipe at room temperature by using electrical capacitance sensor (ECS), then predict the effect of pipeline environment temperature (${\theta}$) on the corrosion rates by designing an efficient artificial neural network (ANN) architecture. ECS consists of number of electrodes mounted on the outer surface of pipeline, the sensor shape, electrode configuration, and the number of electrodes that comprise three key elements of two dimensional capacitance sensors are illustrated. The variation in the dielectric signatures was employed to design electrical capacitance sensor (ECS) with high sensitivity to detect such defects. The rules of 24-electrode sensor parameters such as capacitance, capacitance change, and change rate of capacitance are discussed by ANSYS and MATLAB, which are combined to simulate sensor characteristic. A feed-forward neural network (FFNN) structure are applied, trained and tested to predict the finite element (FE) results of corrosion rates under room temperature, and then used the trained FFNN to predict corrosion rates at different temperature using MATLAB neural network toolbox. The FE results are in excellent agreement with an FFNN results, thus validating the accuracy and reliability of the proposed technique and leads to better understanding of the corrosion mechanism under different pipeline environmental temperature.

• Journal of Power System Engineering
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• v.17 no.2
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• pp.56-62
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• 2013

A technique is presented that uses a circular waveguide for the measurement of the bulk shear (S-wave) velocities of unconsolidated, saturated media, with particular application to near surface soils. The technique requires the measurement of the attenuation characteristics of the fundamental torsional mode that propagate along an embedded pipe, from which the acoustic properties of the surrounding medium are inferred. From the dispersion curve analysis, the feasibility of using fundamental torsional mode which is non-dispersive and have constant attenuation over all frequency range is discussed. The principles behind the technique are discussed and the results of an experimental laboratory validation are presented. The experimental data are best fitted for the different depths of wetted sand and the shear velocities are evaluated as a function of depths. Also the characteristics of the reflected signal from the defects are examined and the reflection coefficients are calculated for identifying the relation between defect sizes and the magnitude of the reflected signal.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.2 s.3
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• pp.23-29
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• 2003

This study is the empirical research about application and evaluation of AVI that is an essential technology for calculating and providing the travel time. Travel time calculation and provision is one of the technique for information collecting and providing in the ITS. Through the field test on a national highway, we proposed the travel time calculation technique from the data by non-contact vehicle detecting method and validated field application performance with field data. We proposed the technique of evaluating field application performance, then using this, analyzed recognition rate, detection rate and travel time with field data.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.86-91
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• 2004

It is very important to detect the bearing defects in rotating machinery since the critical failure of bearing cause a machinery shutdown. However it is difficult to detect the vibration signal resulting from the initial defects of bearing because of the high level of broadband noise. A signal processing technique, called the adaptive line enhancer(ALE) as one of adaptive filter, is studied in this work. This technique is to eliminate broadband noise without a prior knowledge of the noise and signal characteristics. Also we propose the optimal methods for selecting the three main ALE parameters such as correlation length, filter order and adaptation constant used in the adaptative process. Vibration signals for three abnormal bearings, including inner and outer raceways and ball defects, were acquired from Anderon(angular derivative of radius on)meter. The experimental results showed that the proposed technique can reliably detect the bearing defective signals masked by broadband noise.

• Mass Spectrometry Letters
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• v.2 no.2
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• pp.57-60
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• 2011

As background significantly affects measurement accuracy and a detection limit in determination of the trace amounts of uranium, it is necessary to determine the impurities in the Lexan detector film for single particle measurements by thermal ionization mass spectrometry coupled with fission track technique (FT-TIMS). We have prepared various micro sizes of the blank Lexan detector film using a micromanipulation technique for uranium measurements by TIMS. Few tens of fg of uranium background with no remarkable dependency on the film sizes were observed in the blank Lexan films with the sizes from $50{\times}50\;{\mu}m^2$ to $300{\times}300\;{\mu}m^2$. Based on the determination of the uranium background in the Lexan film, any background correction is necessary in the isotopic analysis of a uranium single particle with micron sizes when the particle bearing Lexan film is dissected with less than $300{\times}300\;{\mu}m^2$ size. The isotopic analysis of a uranium particle in U030 standard material using TIMS was carried out to verify the applicability of the Lexan film to the single particle analysis with high accuracy and precision.